Browsing by Author "Belesaca Mendieta, Juan Diego"

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A Comprehensive Ceiling Analysis of the Physical Layer Performance of the 5G NR
(Association for Computing Machinery, Inc, 2023) Belesaca Mendieta, Juan Diego; Vázquez Rodas, Andrés Marcelo; Vázquez Rodas, Andres Marcelo
Modern mobile communication systems, such as Fifth-Generation (5G) technology and beyond 5G, need to exhibit increased capacity, high level of efficiency, improved performance, low end-To-end delay, support to massive number of connections, quality of service and experience, among other requirements. A suboptimal configuration and/or operation of any component of the 5G network can significantly degrade the overall system performance. The physical layer of the radio access network plays a crucial role in the performance of the 5G system. Within this layer, three of the main components that have a significant impact are the characteristics of the propagation channels in which they operate, the synchronization scheme, and the channel estimation accuracy. These components directly influence the system performance and effectiveness. Therefore, this paper presents a comprehensive ceiling analysis of the physical layer of the 5G implemented according to the 3GPP standard. The evaluation of the system encompasses different and standardized channel conditions, synchronization schemes, and channel estimation methods. Rigorous and extensive simulations were conducted using the Matlab 5G NR toolbox for the PDSCH (Physical Downlink Shared Channel). The nodes were configured to operate in both macro-urban and indoor environments. The Clustered Delay Line (CDL) and Tapped Delay Line (TDL) channel models are evaluated under ideal channel estimation and synchronization conditions in each case. Subsequently, more realistic and practical configurations were considered. The simulation results provide quantitative insights of the maximum achievable throughput under various channel environments, including line-of-sight and nonline-of-sight conditions. These results help identify the specific physical layer components that have a greater impact on the throughput of the system. By pinpointing these components, researchers can focus their efforts on developing techniques aimed at enhancing the efficiency of the future beyond 5G networks.
Análisis de techo y evaluación del estándar de la red móvil 5G versión 15 y contribución a la mejora de prestaciones de sistemas móviles de próxima generación mediante técnicas de acceso al medio ortogonales y no ortogonales
(Universidad de Cuenca, 2024-05-21) Belesaca Mendieta, Juan Diego; Vázquez Rodas, Andrés Marcelo
Advancements in next-generation mobile communication systems, such as 5G and its succes- sors, demand meeting a wide array of requirements, including increased capacity, enhanced ef- ficiency, low latency, and support for numerous connections. This study focuses on exhaustively analyzing the physical layer of 5G radio networks, with a particular emphasis on key effects li- ke propagation environments and channels, synchronization, and channel estimation accuracy. Detailed simulations were conducted using the Matlab 5G NR toolbox, assessing various chan- nel conditions and propagation models in both macro-urban and indoor environments. Results reveal that CDL and TDL channel models affect synchronization and channel estimation diffe- rently, underscoring their significance in system performance. This research provides valuable insights for developing techniques to enhance future networks beyond 5G. Additionally, a mul- tiple access management mechanism is proposed, combining orthogonal and non-orthogonal techniques through machine learning to optimize medium access control. The effectiveness of this proposal was evaluated using synthetic traces of human mobility, demonstrating a sig- nificant increase in network access capacity and improvements of up to 42.86 % in random mobility environments and 33.36 % in human behavior-based mobility environments (STEPS). These findings highlight the importance of adopting innovative approaches to maximize mobile network performance, which are crucial for the development of future network technologies.
Análisis del rendimiento de un sistema cooperativo de acceso múltiple ortogonal / no-ortogonal (OMA/NOMA) gestionado mediante una red neuronal artificial
(Universidad de Cuenca, 2021-03-17) Belesaca Mendieta, Juan Diego; Vázquez Rodas, Andrés Marcelo
Next-generation wireless technologies face considerable challenges in terms of providing the required latency and connectivity for new heterogeneous mobile networks. Driven by these problems, this study focuses on increasing user connectivity together with the system general throughput. For doing so, we propose and evaluate a hybrid machine learning-driven orthogonal/non-orthogonal multiple access (OMA/NOMA) system. Specifically, in this work, we use an artificial neural network (ANN) to assign an OMA or NOMA access method to each user equipment (UE). As part of this research we also evaluate the accuracy and training time of the three most relevant learning algorithms of ANN (L-M, BFGS, and OSS). The main objective is to increase the sum-rate of the next generation mobile network in the current beamforming and millimeter-Wave (mm-Wave) channel environment. Simulation results show up to a 20 % sum-rate average performance increase of the system using the ANN management in contrast to a random non-ANN managed system. The LevebergMarquard (L-M) training algorithm is the best overall algorithm for this proposed application as it presents the highest accuracy of around 77 % despite 37 minutes of training, and lower accuracy of 73 % with approximately 28 seconds of training time.
Artificial neural network performance evaluation for a hybrid power domain orthogonal/non-orthogonal multiple access (OMA/NOMA) system
(Association for Computing Machinery, Inc, 2020) Belesaca Mendieta, Juan Diego; Ávila Campos, Pablo Esteban; Vázquez Rodas, Andrés Marcelo
Next-generation wireless technologies face considerable challenges in terms of providing the required latency and connectivity for new heterogeneous mobile networks. Driven by these problems, this study focuses on increasing user connectivity together with system throughput. For doing so, we propose and evaluate a hybrid machine learning-driven orthogonal/non-orthogonal multiple access (OMA/NOMA) system. In this work, we use an artificial neural network (ANN) to assign an OMA or NOMA access method to each user equipment (UE). As part of this research we also evaluate the accuracy and training time of the three most relevant learning algorithms of ANN (L-M, BFGS, and OSS). The main objective is to increase the sum-rate of the mobile network in the introduced beamforming and mmWave channel environment. Simulation results show up to a $20%$ sum-rate average performance increase of the system using the ANN management in contrast to a random non-ANN managed system. The Leveberg-Marquard (L-M) training algorithm is the best overall algorithm for this proposed application as presents the highest accuracy of around $77%$ despite 37 minutes of training and lower accuracy of $73%$ with approximately 28 seconds of training time.
Control de topología en redes inalámbricas de tipo malla con estructura de comunidades
(2018-05-07) Belesaca Mendieta, Juan Diego; Criollo Cumbe, Cristihan Ruben; Vázquez Rodas, Andrés Marcelo
Wireless mesh networks (WMNs) are networks whose main objective is to provide ubiquitous and wireless connectivity to their clients through a set of mesh routers (MR). The WMNs architecture can be classified into 3 groups depending on the functionalities of the nodes: infrastructure, client WMNs, and hybrid wireless mesh networks as a combination of the above. The client WMNs are networks whose management should be as spontaneous as possible. Nowadays, spontaneous networks are emerging as a possible new paradigm of communication, characterized by a strong self-organization and self-maintenance nature. The most common cases are networks formed mainly by mobile devices carried by people. In such spontaneous networks, the devices fulfill both the role of the end user interface, as well as being the traffic router of their peers. Spontaneous networks are usually conformed by portable devices. When these devices are associated with people moving from one place to another, they acquire the human mobility attribute. Most of these networks with such mobility patterns present an organized community structure. Due to technological advance, mobile phones increasingly generate an area of interest for researchers, in order to take advantage of real-time information, to benefit personal and environment care. The combination of such smart devices with social relationships is a reason to incorporate social characteristics into network design strategies. Due to the large number of devices that can exist in these spontaneous networks, there are problems such as: overhead, high probability of packet collision, interference, energy inefficiency, etc. Therefore, arises the need to implement topology control mechanisms that take into account the nodes’s social interaction. Under this context, this project proposes and evaluates three topology control schemes based on centrality metrics in combination with community detection algorithms, for communitystructured WMNs. Each of the evaluated schemes uses a different method for routers selection which will form the network backbone. When evaluating the methods, it is concluded that the Community-Aware Highest Betweenness Centrality Neighbor (C-A HCBN) method achieves the best network connectivity with a reduced number of selected routers for all the mobility models under study. An analysis of the evolution of the reduced topologies is carried out. In all cases, there is an average of less than 50% of nodes that are chosen to fulfill the functions of routers, and the number of times that a node changes its state on average goes from 22 to 41 seconds depending on the mobility model. C-A HCBN is also compared to a previous topology control mechanism which doesn’t consider community structure. The simulation results with real-time traffic (UDP) conclude that our method is better in terms of network performance and energy efficiency. Finally, we propose an additional topology control mechanism based on the minimum spanning tree algorithm. This method manages to obtain smaller topologies than C-A HCBN However, network performance with traffic load is affected by the reduced number of MR in this method. The evaluation of the proposal is carried out by means of extensive simulations using the ns-3 software, a free licensed discrete event network simulator based on C ++, highly diffused and used by the scientific community. The mobility traces are obtained by BonnMotion and SUMO, which are tools for generation and mobility scenario analysis. Generation and visualization of network graphs are obtained with Gephi. Other software that are used for data processing are Octave and Python.
Desarrollo de un dispositivo IoT enfocado a la preservación de archivos bibliográficos patrimoniales en la Biblioteca de la Universidad de Cuenca
(Universidad de Cuenca, 2024-08-26) Vintimilla Jaramillo, Juan Bernardo; Sánchez Cordero, Ricardo Alejandro; Astudillo Salinas, Darwin Fabián; Belesaca Mendieta, Juan Diego
Heritage books are essential historical and cultural archives that preserve the knowledge and stories of past civilizations, being fundamental for education and academic research. Due to their organic composition, historical documents are susceptible to deterioration caused by environmental factors such as humidity, temperature, and air quality. In this work, an IoT device was developed to monitor and optimize the care of heritage bibliographic archives at the Central Library of the University of Cuenca. The proposed device utilized an ESP32 SoC and various sensors: DHT22 for temperature and humidity, SDS011 for air quality, and SE045 for water level in a dehumidifier tank. These sensors allow measuring and recording the mentioned variables. Additionally, a Docker container of the Thingsboard platform was implemented to simplify the IoT platform and dashboard deployment. The collected data was transmitted via HTTPS to the Thingsboard platform. The result of the implementation allowed library staff to monitor conditions in real time, receive alerts for anomalies, and facilitate preventive measures to preserve the documents. As well, a significant improvement in the maintenance required for the conservation of heritage documents was observed, reducing the need for frequent manual interventions in restricted areas. This solution can be easily implemented and adapted in all heritage rooms of the University of Cuenca and other libraries, contributing to cultural and academic heritage preservation.
Topological Evaluation of Realistic Mobility Models for Spontaneous Wireless Networks Using Graph Theory Metrics
(Association for Computing Machinery, Inc, 2023) Belesaca Mendieta, Juan Diego; Avilés Parra, Pablo Felipe; Vázquez Rodas, Andrés Marcelo; Astudillo Salinas, Darwin Fabián; Pinto Nieto, Josué David
In recent years, the exponential growth of mobile devices connected to access networks has led to the emergence of connection architectures characterized by a high density of end devices. This, in turn, has posed significant challenges in access management. As a result, the scientific community is increasingly recognizing the crucial need to develop equitable and unbiased access control mechanisms. A fundamental starting point is to conduct a comprehensive analysis of these massive end-device architectures, treating them as high-density graphs of interconnected nodes. In this work, we generated massive topologies/architectures using synthetic models of human mobility that accurately reflect real-world human behavior. Subsequently, we evaluated and compared these topologies using six key metrics derived from graph theory. Additionally, we established connections between nodes within each topology based on the concept of spontaneous Wireless Mesh Networks. The outcomes of our analysis shed light on mobility models that demonstrated superior performance in specific metrics, while also proposing a methodology to effectively characterize these mobility models
Transformación digital: modernización del sistema de registro hidrometeorológico del PROMAS
(Universidad de Cuenca, 2024-08-27) Maldonado Tuza, Henry David; Mogrovejo Nieves, Kevin Ismael; Astudillo Salinas, Darwin Fabián; Belesaca Mendieta, Juan Diego
In this work, a hydrometeorological data logging device is designed and implemented, integrating LoRa technology into an ESP32-S3 microcontroller. The device consists of two PCB modules: the first includes connection ports for station and general-purpose sensors, an ADC module, a counter, an RTC module, and a power switch; the second module integrates the ESP32 microcontroller and the LoRa chip. The software is designed to minimize power consumption by reducing the CPU operating frequency, using Deep Sleep mode, and implementing the VMTP frame model. Measurements of temperature, humidity, wind speed and direction, precipitation, solar radiation, and UV radiation, as well as information on sensor operation and the time of measurements, are sent to the TTS server using the LoRaWAN network protocol, to later establish communication with Thingsboard and present the information in a dashboard. The device demonstrated good performance in field tests, enabling the collection and validation of environmental monitoring data.